Skip to main content

Please enter a keyword and click the arrow to search the site

Optimal sampling strategies in the coupon collectors problem with unknown population size

Journal

Annals of Operations Research

Subject

Management Science and Operations

Publishing details

Annals of Operations Research 2015 Vol 233:1 p 77-99

Authors / Editors

Dobson G;Tezcan T

Publication Year

2015

Abstract

In doing a six-sigma analysis of a process one must first determine the set of possible factors that potentially drive the response of interest. This stage of the the work, known as process mapping, is time consuming. Spending too much time on it wastes investigators and employees time. Yet, spending too little time may result in failing to uncover important factors that drive the process. We model this situation as a general coupon collector’s problem with N distinct coupons, where the exact value of N is not known. Our objective is to devise effective strategies to minimize the total cost incurred due to sampling in addition to the cost of unidentified coupons when the collector stops sampling. We propose a policy based on an asymptotic analysis when N is large and prove that the proposed policy is asymptotically optimal. We also illustrate the effectiveness of this policy with numerical experiments.

Keywords

Coupon collector’s problem; Asymptotic analysis; Stochastic processes; Optimization

Available on ECCH

No


Select up to 4 programmes to compare

Select one more to compare
×
subscribe_image_desktop 5949B9BFE33243D782D1C7A17E3345D0

Sign up to receive our latest news and business thinking direct to your inbox

×

Sign up to receive our latest course information and business thinking

Leave your details above if you would like to receive emails containing the latest thought leadership, invitations to events and news about courses that could enhance your career. If you would prefer not to receive our emails, you can still access the case study by clicking the button below. You can opt-out of receiving our emails at any time by visiting: https://london.edu/my-profile-preferences or by unsubscribing through the link provided in our emails. View our Privacy Policy for more information on your rights.